A Robust UWSN Handover Prediction System Using Ensemble Learning.

The use of underwater wireless sensor networks (UWSNs) for collaborative monitoring and marine data collection tasks is rapidly increasing. One of the major challenges associated with building these networks is handover prediction; this is because the mobility model of the sensor nodes is different from that of ground-based wireless sensor network (WSN) devices. Therefore, handover prediction is the focus of the present work. There have been limited efforts in addressing the handover prediction problem in UWSNs and in the use of ensemble learning in handover prediction for UWSNs. Hence, we propose the simulation of the sensor node mobility using real marine data collected by the Korea Hydrographic and Oceanographic Agency. These data include the water current speed and direction between data. The proposed simulation consists of a large number of sensor nodes and base stations in a UWSN. Next, we collected the handover events from the simulation, which were utilized as a dataset for the handover prediction task. Finally, we utilized four machine learning prediction algorithms (i.e., gradient boosting, decision tree (DT), Gaussian naive Bayes (GNB), and K-nearest neighbor (KNN)) to predict handover events based on historically collected handover events. The obtained prediction accuracy rates were above 95%. The best prediction accuracy rate achieved by the state-of-the-art method was 56% for any UWSN. Moreover, when the proposed models were evaluated on performance metrics, the measured evolution scores emphasized the high quality of the proposed prediction models. While the ensemble learning model outperformed the GNB and KNN models, the performance of ensemble learning and decision tree models was almost identical

Marine Data Prediction: An Evaluation of Machine Learning, Deep Learning, and Statistical Predictive Models.

Nowadays, ocean observation technology continues to progress, resulting in a huge increase in marine data volume and dimensionality. This volume of data provides a golden opportunity to train predictive models, as the more the data is, the better the predictive model is. Predicting marine data such as sea surface temperature (SST) and Significant Wave Height (SWH) is a vital task in a variety of disciplines, including marine activities, deep-sea, and marine biodiversity monitoring. The literature has efforts to forecast such marine data; these efforts can be classified into three classes: machine learning, deep learning, and statistical predictive models. To the best of the authors' knowledge, no study compared the performance of these three approaches on a real dataset. This paper focuses on the prediction of two critical marine features: the SST and SWH. In this work, we proposed implementing statistical, deep learning, and machine learning models for predicting the SST and SWH on a real dataset obtained from the Korea Hydrographic and Oceanographic Agency. Then, we proposed comparing these three predictive approaches on four different evaluation metrics. Experimental results have revealed that the deep learning model slightly outperformed the machine learning models for overall performance, and both of these approaches greatly outperformed the statistical predictive model

Uterine sparing approaches in management of placenta accreta: a summarized review

Placenta accreta is a potentially life-threatening obstetric condition that required multidisciplinary approach to management. Placenta accreta occurs in complete absence of the decidua basalis. Women with previous cesarean section delivery or placenta previa are known to be at greater risk of placenta accreta. A previous study reported that 24%& 67% increase in the incidence of placenta accreta in women 1 versus 3 or more previous cesarean deliveries respectively. Antenatal diagnosis of placental invasion has the potential to improve maternal and fetal outcomes. In practice, incomplete non-separation of the placenta at delivery leads to massive obstetric hemorrhage resulting in maternal morbidities such as massive blood transfusion, DIC, injury to the bladder and intestines and the need for hysterectomy. Sonographic examination with gray scale and color doppler imaging is the recommended first line modality for diagnosis of morbidly adherent placenta. Techniques developed for conservative management are techniques developed to preserve uterus and future fertility which is crucially linked to societal status and self-esteem

THE PRACTICE AND PERCEPTION OF HOSPITAL PHARMACISTS TOWARDS ERRORS IN DISPENSING MEDICINES AND THEIR POSSIBLE CAUSES IN OMDURMAN MILITARY HOSPITAL, SUDAN

Introduction: Hospital pharmacies dispensing errors are common and investigating them for identifying factors involved in it and developing strategies to minimize their occurrence. Errors can arise at any stage during the dispensing process. Dispensing errors were identified by checking the prescribed drug against the dispensed medication. Materials and Methods: A cross sectional study involving 100 pharmacists who were administered a survey research designed to assess pharmacists' attitudes, factors associated with DEs and involvement in DE, conducted between 1st January 2019 and 1st February 2019 at Omdurman Military Hospital (OMH) Pharmacies. A data analyzed by Statistical Package for Social Sciences software version 21. Results: 55% from the pharmacists in the study have poor attitude toward dispensing errors. The most common factors influencing dispensing errors as stated by participants were lack of therapeutic training (stated by 81%), 62% from the participants stated that workload and time pressure are causes of dispensing errors in area of factors associated with the work environment. 48% from the pharmacists in the study committing dispensing errors, 41.7% from them committed dispensing errors once while 23% committed fourth or more. Conclusion: With the multiplicity of risk factors in our environment, there is urgent need to reinforce the training of pharmacists and the provision of resource materials and enabling work environment aimed at minimizing medication errors.                                  Peer Review History: Received: 8 September 2020; Revised: 7 October; Accepted: 20 October, Available online: 15 November 2020 Academic Editor: Dr. Tamer Elhabibi, Suez Canal University, Egypt, [email protected] UJPR follows the most transparent and toughest ‘Advanced OPEN peer review’ system. The identity of the authors and, reviewers will be known to each other. This transparent process will help to eradicate any possible malicious/purposeful interference by any person (publishing staff, reviewer, editor, author, etc) during peer review. As a result of this unique system, all reviewers will get their due recognition and respect, once their names are published in the papers. We expect that, by publishing peer review reports with published papers, will be helpful to many authors for drafting their article according to the specifications. Auhors will remove any error of their article and they will improve their article(s) according to the previous reports displayed with published article(s). The main purpose of it is ‘to improve the quality of a candidate manuscript’. Our reviewers check the ‘strength and weakness of a manuscript honestly’. There will increase in the perfection, and transparency. Received file:                Reviewer's Comments: Average Peer review marks at initial stage: 5.0/10 Average Peer review marks at publication stage: 7.0/10 Reviewer(s) detail: Prof. Dr. Hassan A.H. Al-Shamahy, Sana'a University, Yemen, [email protected]   Dr. A.A. Mgbahurike, University of Port Harcourt, Nigeria, [email protected] Similar Articles: AWARENESS OF PHARMACISTS TOWARDS ASPARTAME SIDE EFFECTS IN KHARTOUM CITY, SUDA

Experimental antibacterial activity of selective cyclooxygenase antagonist

Background: From the history of the development of pharmaceutical compounds it is evident that any drug may have the possibility of possessing diverse functions and thus may have useful activity in completely different fields of medicine and different studies showed that newer antimicrobials have revealed antimicrobial action involved in the management of diseases of non-infectious etiology. This study was done to determine in vitro antibacterial activity of selected selective cyclooxygenase-2 inhibitor.Methods: Twenty two strains of gram positive and gram negative bacteria, which were isolated from skin and urinary tract infected patient. These bacteria were being cultured on specific optimal growth media. The antibacterial activity of selective COX-2 (meloxicam, celecoxib, valdecoxib and nimesulide). Inhibitors determined by measuring zone of inhibition and minimal inhibitory concentration (MIC).Results: Results showed that MIC of celecoxib and meloxicam in µg/ml was ranged from 5-80µg/ml on selected bacteria compared with negative control distilled water (D.W) ,valdecoxib was 80-160µg/ml, while and nimesulide was ranged from 5-40 µg/ml .All the selected bacteria were showed sensitivity for all coxib used in this experimental study except Pseudomonas aeruginosa which showed resistant to meloxicam and valdecoxib, Klebsiella pneumoniae resist to nimesulide while Staphylococcus aureus was resist to valdecoxib. The smaller zone of inhibition showed by valdecoxib and celecoxib which was 3mm against Klebsiella pneumoniae, while the larger zone of inhibition showed by nimesulide which was 26mm against Escherichia coli.Conclusions: In conclusion selective cyclooxygenase (cox-2) inhibitor possesses antibacterial activity this is especially for nimesulide and little by valdecoxib. Escherichia coli are sensitive bacteria to all coxib. Consequently; coxib may be regarded as anti-inflammatory and antibacterial agent especially for urinary tract infection where Escherichia coli are the major causative organism

The Effectiveness of Task-Based Instruction on the Reading Comprehension Ability of EFL Students at the University of Tabuk

The present study examined the effectiveness of task-based instruction (TBI) in improving the reading comprehension ability of EFL students at the University of Tabuk. In order to conduct this study, 80 EFL students at the University of Tabuk, who have taken Placement Test (TUPT) as a pre-test, were chosen for the study. The participants of the study were selected randomly. The researcher used reading comprehension tasks and Placebo Task (Pre- / Post-test) as the research instruments of the study. The findings of this study revealed that students in the experimental group outperformed students in the control group. Thus, task-based instruction was considered to be effective in increasing the reading comprehension ability. Keywords: Tasks, Language learning development, Reading comprehension, EFL students DOI: 10.7176/JLLL/54-02 Publication date:March 31st 2019

Epidemiology of urinary tract infections and antibiotics sensitivity among pregnant women at Khartoum North Hospital

<p>Abstract</p> <p>Background</p> <p>Urinary tract infections (UTI) can lead to poor maternal and perinatal outcomes. Investigating epidemiology of UTI and antibiotics sensitivity among pregnant women is fundamental for care-givers and health planners.</p> <p>Methods</p> <p>A cross sectional study has been conducted at Khartoum north teaching hospital Antenatal Care Clinic between February-June 2010, to investigate epidemiology of UTI and antibiotics resistance among pregnant women. Structured questionnaires were used to gather data from pregnant women. UTI was diagnosed using mid stream urine culture on standard culture media</p> <p>Results</p> <p>Out of 235 pregnant women included, 66 (28.0%) were symptomatic and 169 (71.9%) asymptomatic. the prevalence of bacteriuria among symptomatic and asymptomatic pregnant women were (12.1%), and (14.7%) respectively, with no significant difference between the two groups (<it>P </it>= 0.596), and the overall prevalence of UTI was (14.0%). In multivariate analyses, age, gestational age, parity, and history of UTI in index pregnancy were not associated with bacteriuria. <it>Escherichia coli </it>(42.4%) and <it>S. aureus </it>(39.3%) were the commonest isolated bacteria. Four, 2, 2, 3, 4, 2 and 0 out of 14 <it>E. coli </it>isolates, showed resistance to amoxicillin, naladixic acid, nitrofurantoin, ciprofloxacin, co-trimoxazole, amoxicillin/clavulanate and norfloxacin, respectively</p> <p>Conclusion</p> <p><it>Escherichia coli </it>were the most prevalent causative organisms and showing multi drug resistance pattern, asymptomatic bacteriuria is more prevalent than symptomatic among pregnant women. Urine culture for screening and diagnosis purpose for all pregnant is recommended.</p

Comparison of Naïve Bayes Algorithm and Decision Tree C4.5 for Hospital Readmission Diabetes Patients using HbA1c Measurement

Diabetes is a metabolic disorder disease in which the pancreas does not produce enough insulin or the body cannot use insulin produced effectively. The HbA1c examination, which measures the average glucose level of patients during the last 2-3 months, has become an important step to determine the condition of diabetic patients. Knowledge of the patient's condition can help medical staff to predict the possibility of patient readmissions, namely the occurrence of a patient requiring hospitalization services back at the hospital. The ability to predict patient readmissions will ultimately help the hospital to calculate and manage the quality of patient care. This study compares the performance of the Naïve Bayes method and C4.5 Decision Tree in predicting readmissions of diabetic patients, especially patients who have undergone HbA1c examination. As part of this study we also compare the performance of the classification model from a number of scenarios involving a combination of preprocessing methods, namely Synthetic Minority Over-Sampling Technique (SMOTE) and Wrapper feature selection method, with both classification techniques. The scenario of C4.5 method combined with SMOTE and feature selection method produces the best performance in classifying readmissions of diabetic patients with an accuracy value of 82.74 %, precision value of 87.1 %, and recall value of 82.7 %

Optimum conditions for ascorbic acid determination in three Iraqi citrus using HPLC technique

A high-performance liquid chromatography method was employed for the quantitative determination of ascorbic acid (AA) which called vitamin C in three types of Iraqi citrus (orange mandarin and aurantium ) and to establish this goal , evaluation of ascorbic acid degradation is so important due to its significant criticality when exposure to ordinary atmospheric conditions. The chromatographic analysis of AA was carried out after their sequential elution with KH2PO4 ( as mobile phase) by reverse-phase HPLC technique with C8 column and UV detection at 214 nm. .Bad resolutions was appeared clearly for C8 column , so another alternative condition were carried out to improve the resolution by replacement of C8 by C18 column .Statistical treatments were used to calculate relative standard deviation (RSD%) for the results to gain acceptable confidence to the present work , so the linearity of calibration curve, accuracy, and repeatability of this method are all satisfactory